#ai and learning

[elexuscal]

"what did students do before chatgpt?" well one time i forgot i had a history essay due at my 10am class the morning of so over the course of my 30 minute bus ride to school i awkwardly used by backpack as a desk, sped wrote the essay, and got an A on it.

six months later i re-read the essay prior to the final exam, went 'ohhhh yeah i remember this', got a question on that topic, and aced it.

point being that actually doing the work is how you learn the material and internalize it. ChatGPT can give you a short cut but it won't build you the the muscles.

[destiel-news-network]

(Source)

[inkskinned]

i love you vaccines i love you research i love you reading the book instead of having chatgpt summarize it i love you critically thinking rather than reacting to a headline i love you investigating the source material i love you science i love you math even though you are personally my enemy (math/yn slowburn) i love you writing even though you try to stab me a lot i love you Experts in Your Field i love you Using The Brain

[richardtheteacher]

AI Dolls and Digital Desks: High School Teaching in 2025

An article by Richard James Rogers��(Award-Winning Author of The Quick Guide to Classroom Management and The Power of Praise: Empowering Students Through Positive Feedback). This blog post is illustrated by Pop Sutthiya Lertyongphati. Don’t forget to check out the full bibliography and recommended reading list at the end of this blog post. Artificial Intelligence (AI) used to sound like science…

[monsoon-of-art]

[0sbrain]

alternatives for ai to design ocs

hero forge

picrew

the fucking sims 4

your local furry artist

bitmoji

shitty photoshoped collage

DeviantArt bases

zepeto

making edits of your favorite character

searching "dress up game" on the app store

learning how to draw

[microlearningplatform]

AI-Powered Microlearning in Pharma: Revolutionizing Training and Compliance | MaxLearn

The pharmaceutical industry operates in one of the most complex and regulated environments, where continuous learning and up-to-date knowledge are critical to success. From navigating intricate regulations and compliance requirements to keeping up with fast-evolving scientific advancements, professionals in the pharmaceutical sector are under constant pressure to stay informed and skilled. Traditional training methods, however, often fall short in meeting these demands, being time-consuming, costly, and difficult to personalize.

Enter AI-powered microlearning, an innovative solution that is transforming how the pharmaceutical industry approaches learning and development. Combining the principles of microlearning—delivering short, focused lessons with an emphasis on engagement and retention—with the power of artificial intelligence (AI), this new approach offers personalized, adaptive, and highly efficient learning experiences. In this article, we explore how AI-powered microlearning is revolutionizing training in the pharmaceutical sector, from compliance to workforce development.

The Challenges of Pharmaceutical Training

Pharmaceutical companies face unique challenges when it comes to employee training:

Regulatory Compliance: The industry is heavily regulated, with organizations needing to comply with strict standards from bodies such as the FDA, EMA, and other global regulatory agencies. Employees must continuously update their knowledge to remain compliant.

Complex Subject Matter: Pharma professionals deal with highly complex topics, from drug development and clinical trials to pharmacovigilance and biotech innovations. Mastery of this knowledge is critical to success.

Rapidly Changing Knowledge: With scientific and technological advancements happening at an unprecedented rate, pharmaceutical employees must keep pace with new discoveries, techniques, and treatments.

Global Workforce: Many pharmaceutical companies operate globally, meaning training programs need to accommodate diverse teams across multiple geographies, cultures, and languages.

Traditional training approaches such as classroom-based sessions, lengthy eLearning modules, and static learning management systems (LMS) struggle to meet these challenges. AI-powered microlearning, on the other hand, offers a flexible, targeted, and dynamic solution.

What is AI-Powered Microlearning?

Microlearning refers to a method of delivering content in short, easily digestible segments, typically no longer than 10 minutes. It is designed to address specific learning objectives and can be accessed on-demand, often through mobile devices. This approach makes it easier for learners to absorb and retain information while offering flexibility to fit into their busy schedules.

When combined with artificial intelligence, microlearning becomes even more powerful. AI algorithms analyze user behavior, learning patterns, and preferences to deliver highly personalized content. The system can adapt in real-time, providing learners with the right content at the right time, ensuring that learning is relevant and effective. AI can also track performance, identify knowledge gaps, and offer targeted remediation to ensure learners achieve mastery.

Benefits of AI-Powered Microlearning in Pharma

The application of AI-powered microlearning in the pharmaceutical industry offers numerous benefits:

1. Personalized Learning Paths

AI-powered microlearning systems, such as MaxLearn, use AI algorithms to create personalized learning paths for each user. Whether an employee needs to brush up on specific compliance regulations or develop expertise in a new drug discovery process, the system tailors the content to meet their unique needs. This reduces the amount of time spent on irrelevant material and enhances engagement by offering content that directly aligns with the learner’s goals.

2. Improved Knowledge Retention

Microlearning is built on the concept of delivering information in small, bite-sized chunks, which is proven to improve knowledge retention. AI further enhances this by delivering spaced repetition, a technique that involves revisiting key concepts over time to reinforce learning. In the pharmaceutical industry, where critical knowledge must be retained and applied correctly, this is especially valuable.

3. Compliance Training Made Easy

Staying compliant with regulatory guidelines is a top priority in pharma, and AI-powered microlearning simplifies compliance training. Instead of overwhelming employees with long, annual training sessions, microlearning breaks down compliance topics into manageable modules that can be accessed anytime, anywhere. AI ensures that employees receive regular, personalized reminders and updates about compliance issues, helping them stay informed and audit-ready.

4. On-Demand Learning for a Global Workforce

Pharmaceutical companies often have a global workforce, which requires training programs that are accessible across different time zones and in multiple languages. AI-powered microlearning platforms are mobile-friendly and can be accessed on-demand, making it easy for employees to learn when and where it’s most convenient for them. Furthermore, AI can provide language translations and cultural adaptations to ensure training is relevant for a global audience.

5. Cost and Time Efficiency

Traditional training programs often involve high costs and lengthy durations, which can disrupt business operations. AI-powered microlearning, however, offers a cost-effective solution. It eliminates the need for travel, classroom setups, and long training hours. Instead, learners can complete short modules during their regular workday without compromising productivity.

6. Real-Time Analytics and Insights

One of the most powerful aspects of AI-powered microlearning is its ability to provide real-time analytics. AI can track learners' progress, engagement levels, and performance. This data allows managers and L&D professionals to identify knowledge gaps, measure the effectiveness of training programs, and make data-driven decisions to improve future training initiatives.

AI-Powered Microlearning for Pharma: Use Cases

AI-powered microlearning can be applied across various training scenarios in the pharmaceutical industry. Some key use cases include:

1. Regulatory Compliance Training

Ensuring that employees understand and comply with industry regulations is crucial. AI-powered microlearning can deliver short, focused modules on topics like Good Manufacturing Practices (GMP), FDA regulations, and pharmacovigilance. The system can monitor learner progress and provide updates when regulatory changes occur, keeping employees compliant and audit-ready.

2. Product Knowledge and Sales Training

In the pharmaceutical industry, sales representatives need to stay updated on the latest product developments, clinical trial results, and competitor products. Microlearning allows sales teams to quickly access the information they need, such as new drug features or key talking points, before meeting with healthcare professionals.

3. Onboarding for New Hires

Onboarding in pharma can be overwhelming due to the complex nature of the industry. AI-powered microlearning platform simplifies the onboarding process by delivering short, digestible lessons that introduce new employees to company policies, safety protocols, and product lines. This helps new hires get up to speed faster and more effectively.

4. Continuous Professional Development (CPD)

With rapid advancements in medical science and technology, pharmaceutical professionals need to continuously update their knowledge. AI-powered microlearning can provide ongoing CPD by delivering bite-sized modules on new drug research, medical breakthroughs, and innovative treatments.

5. Soft Skills Development

In addition to technical knowledge, pharma professionals also need strong communication, leadership, and collaboration skills. AI-powered microlearning platforms can offer soft skills training through interactive scenarios, quizzes, and gamified lessons, helping employees improve their interpersonal skills in a pharma-specific context.

MaxLearn: The Future of AI-Powered Microlearning in Pharma

As a leading AI-powered microlearning platform, MaxLearn is uniquely positioned to meet the needs of the pharmaceutical industry. MaxLearn offers:

Personalized Learning Paths tailored to each individual’s learning style and knowledge gaps.

Gamified Learning to keep learners engaged and motivated.

Real-Time Analytics to monitor progress and performance.

Compliance-Ready Content that meets industry standards and regulations.

Mobile-First Design, allowing learners to access content anywhere, anytime.

MaxLearn’s cutting-edge technology empowers pharmaceutical companies to streamline training, enhance employee skills, and maintain compliance in an ever-evolving landscape.

Conclusion

AI-powered microlearning represents a game-changing solution for the pharmaceutical industry. With its ability to deliver personalized, adaptive learning experiences, it addresses the specific challenges faced by pharma professionals, from compliance and regulatory training to continuous professional development. MaxLearn, with its AI-driven platform, is at the forefront of this transformation, providing the tools and insights needed to revolutionize training and development in pharma.

As the pharmaceutical industry continues to evolve, AI-powered microlearning will play a crucial role in ensuring that employees stay informed, skilled, and compliant, driving better business outcomes and fostering innovation.

[kylominis]

touchy feely mornings with mr. clingy [♡]

[eerieeccentrix]

Black Bat Flower

(tacca chantrieri)

[bitchesgetriches]

31% of employees are actively ‘sabotaging’ AI efforts. Here’s why

"In a new study, almost a third of respondents said they are refusing to use their company’s AI tools and apps. A few factors could be at play."

[river-taxbird]

AI hasn't improved in 18 months. It's likely that this is it. There is currently no evidence the capabilities of ChatGPT will ever improve. It's time for AI companies to put up or shut up.

I'm just re-iterating this excellent post from Ed Zitron, but it's not left my head since I read it and I want to share it. I'm also taking some talking points from Ed's other posts. So basically:

We keep hearing AI is going to get better and better, but these promises seem to be coming from a mix of companies engaging in wild speculation and lying.

Chatgpt, the industry leading large language model, has not materially improved in 18 months. For something that claims to be getting exponentially better, it sure is the same shit.

Hallucinations appear to be an inherent aspect of the technology. Since it's based on statistics and ai doesn't know anything, it can never know what is true. How could I possibly trust it to get any real work done if I can't rely on it's output? If I have to fact check everything it says I might as well do the work myself.

For "real" ai that does know what is true to exist, it would require us to discover new concepts in psychology, math, and computing, which open ai is not working on, and seemingly no other ai companies are either.

Open ai has already seemingly slurped up all the data from the open web already. Chatgpt 5 would take 5x more training data than chatgpt 4 to train. Where is this data coming from, exactly?

Since improvement appears to have ground to a halt, what if this is it? What if Chatgpt 4 is as good as LLMs can ever be? What use is it?

As Jim Covello, a leading semiconductor analyst at Goldman Sachs said (on page 10, and that's big finance so you know they only care about money): if tech companies are spending a trillion dollars to build up the infrastructure to support ai, what trillion dollar problem is it meant to solve? AI companies have a unique talent for burning venture capital and it's unclear if Open AI will be able to survive more than a few years unless everyone suddenly adopts it all at once. (Hey, didn't crypto and the metaverse also require spontaneous mass adoption to make sense?)

There is no problem that current ai is a solution to. Consumer tech is basically solved, normal people don't need more tech than a laptop and a smartphone. Big tech have run out of innovations, and they are desperately looking for the next thing to sell. It happened with the metaverse and it's happening again.

In summary:

Ai hasn't materially improved since the launch of Chatgpt4, which wasn't that big of an upgrade to 3.

There is currently no technological roadmap for ai to become better than it is. (As Jim Covello said on the Goldman Sachs report, the evolution of smartphones was openly planned years ahead of time.) The current problems are inherent to the current technology and nobody has indicated there is any way to solve them in the pipeline. We have likely reached the limits of what LLMs can do, and they still can't do much.

Don't believe AI companies when they say things are going to improve from where they are now before they provide evidence. It's time for the AI shills to put up, or shut up.

[kawareo]

"AI does this better than me :("

"My work is never as good as AI's :("

"I have to use AI to be good :("

you're devaluing yourself. AI is not smart, it's not creative, it just has access to the whole internet at once (which btw includes all the wrong things), and guess what, so do you. You're better than the plagiarism machine and you've been lied to and told that it's smarter than you and I hope you stop believing that because you deserve better

[inkskinned]

i have chronic pain. i am neurodivergent. i understand - deeply - the allure of a "quick fix" like AI. i also just grew up in a different time. we have been warned about this.

15 entire years ago i heard about this. in my forensics class in high school, we watched a documentary about how AI-based "crime solving" software was inevitably biased against people of color.

my teacher stressed that AI is like a book: when someone writes it, some part of the author will remain within the result. the internet existed but not as loudly at that point - we didn't know that AI would be able to teach itself off already-biased Reddit threads. i googled it: yes, this bias is still happening. yes, it's just as bad if not worse.

i can't actually stop you. if you wanna use ChatGPT to slide through your classes, that's on you. it's your money and it's your time. you will spend none of it thinking, you will learn nothing, and, in college, you will piss away hundreds of thousands of dollars. you will stand at the podium having done nothing, accomplished nothing. a cold and bitter pyrrhic victory.

i'm not even sure students actually read the essays or summaries or emails they have ChatGPT pump out. i think it just flows over them and they use the first answer they get. my brother teaches engineering - he recently got fifty-three copies of almost-the-exact-same lab reports. no one had even changed the wording.

and yes: AI itself (as a concept and practice) isn't always evil. there's AI that can help detect cancer, for example. and yet: when i ask my students if they'd be okay with a doctor that learned from AI, many of them balk. it is one thing if they don't read their engineering textbook or if they don't write the critical-thinking essay. it's another when it starts to affect them. they know it's wrong for AI to broad-spectrum deny insurance claims, but they swear their use of AI is different.

there's a strange desire to sort of divorce real-world AI malpractice over "personal use". for example, is it moral to use AI to write your cover letters? cover letters are essentially only templates, and besides: AI is going to be reading your job app, so isn't it kind of fair?

i recently found out that people use AI as a romantic or sexual partner. it seems like teenagers particularly enjoy this connection, and this is one of those "sticky" moments as a teacher. honestly - you can roast me for this - but if it was an actually-safe AI, i think teenagers exploring their sexuality with a fake partner is amazing. it prevents them from making permanent mistakes, it can teach them about their bodies and their desires, and it can help their confidence. but the problem is that it's not safe. there isn't a well-educated, sensitive AI specifically to help teens explore their hormones. it's just internet-fed cycle. who knows what they're learning. who knows what misinformation they're getting.

the most common pushback i get involves therapy. none of us have access to the therapist of our dreams - it's expensive, elusive, and involves an annoying amount of insurance claims. someone once asked me: are you going to be mad when AI saves someone's life?

therapists are not just trained on the book, they're trained on patient management and helping you see things you don't see yourself. part of it will involve discomfort. i don't know that AI is ever going to be able to analyze the words you feed it and answer with a mind towards the "whole person" writing those words. but also - if it keeps/kept you alive, i'm not a purist. i've done terrible things to myself when i was at rock bottom. in an emergency, we kind of forgive the seatbelt for leaving bruises. it's just that chat shouldn't be your only form of self-care and recovery.

and i worry that the influence chat has is expanding. more and more i see people use chat for the smallest, most easily-navigated situations. and i can't like, make you worry about that in your own life. i often think about how easy it was for social media to take over all my time - how i can't have a tiktok because i spend hours on it. i don't want that to happen with chat. i want to enjoy thinking. i want to enjoy writing. i want to be here. i've already really been struggling to put the phone down. this feels like another way to get you to pick the phone up.

the other day, i was frustrated by a book i was reading. it's far in the series and is about a character i resent. i googled if i had to read it, or if it was one of those "in between" books that don't actually affect the plot (you know, one of those ".5" books). someone said something that really stuck with me - theoretically you're reading this series for enjoyment, so while you don't actually have to read it, one would assume you want to read it.

i am watching a generation of people learn they don't have to read the thing in their hand. and it is kind of a strange sort of doom that comes over me: i read because it's genuinely fun. i learn because even though it's hard, it feels good. i try because it makes me happy to try. and i'm watching a generation of people all lay down and say: but i don't want to try.

[maodun]

shout out to machine learning tech (and all the human-input adjustment contributors) that's brought about the present developmental stage of machine translation, making the current global village 地球村 moment on rednote小红书 accessible in a way that would not have been possible years ago.

[saveahorserideaneddie]

scrolling buddie fics on ao3: oh hey this fic looks-

tags: this fic was written using chatgpt

me: